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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In statistics, simple linear regression is the least squares estimator of a linear regression model with a single predictor variable. In other words, simple linear regression fits a straight line through the set of n points in such a way that makes the sum of squared residuals of the model (that is, vertical distances between the points of the data set and the fitted line) as small as possible. The adjective simple refers to the fact that this regression is one of the…mehr

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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In statistics, simple linear regression is the least squares estimator of a linear regression model with a single predictor variable. In other words, simple linear regression fits a straight line through the set of n points in such a way that makes the sum of squared residuals of the model (that is, vertical distances between the points of the data set and the fitted line) as small as possible. The adjective simple refers to the fact that this regression is one of the simplest in statistics. The fitted line has the slope equal to the correlation between y and x corrected by the ratio of standard deviations of these variables.